Determining the classification of dry beans using WEKA
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The significant variety in bean shape and size makes dry bean classification a difficult task. Traditional categorization procedures, such as hand sorting, are time-consuming and labor-intensive. Machine learning approaches appear to be a potential option for dry bean classification. A machine learning classification approach for dry beans using WEKA was offered in this research. The approach employs Multilayer Perceptron (MLP), Support Vector Machine (SVM), k-Nearest Neighbors (kNN), and Decision Tree (DT) machine learning algorithms.
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Determining the classification of dry beans using WEKA
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